Hierarchical Regression Models for Interviewer and Respondent Effects

Abstract

It is generally recognized that interviewers may have an important effect on the quality of the data collected in survey research. This article presents an application of the hierarchical regression model in the analysis of interviewer effects. The hierarchical regression model offers an elegant way of analyzing the simultaneous effects of specific interviewer and respondent characteristics. It is especially attractive if the research design does not provide for a random assignment of respondents to interviewers, because it allows the researcher to use statistical rather than experimental control by modeling the interviewer effects conditional on the respondent effects.